冬小麦返青期冠层光谱特性分析  

Spectral Characteristics of Winter Wheat Canopy at Returning Green Stage

作　　者：李树强[1] 

机构地区：[1]河南科技大学农业工程学院,河南洛阳471003

出　　处：《贵州农业科学》2014年第2期65-68,共4页Guizhou Agricultural Sciences

基　　金：河南省教育厅科学研究计划"牡丹红斑病单叶光谱特性研究及严重度反演"(13A416231)

摘　　要：为了对冬小麦的精准化管理提供理论依据,于冬小麦的返青期测量了冠层叶片反射光谱,获取了反射光谱的一阶导数曲线,分析曲线的局部极值及其对应的反射率与叶绿素含量之间的关系,构建了植被指数,根据各指标构建叶绿素含量的预测模型,对比模型的预测效果,结合GPS信息进行了空间预测能力的分析。结果表明:返青期的小麦冠层叶片反射光谱的一阶导数光谱存在多个局部极值,根据局部极值构建的反射率和植被指数对叶绿素含量的预测模型具有较好的预测效果,其中,利用冠层光谱曲线的"绿峰"和"红谷"构建的NDVI(λgreen,λrd)预测模型,预测R2达0.743 5,满足单点预测的需要。空间分析表明,以"绿峰"Rλgreen和植被指数NDVI(λgreen,λrd)构建的预测模型均具有一定的空间预测能力,NDVI(λgreen,λrd)的空间预测能力较好,能够反映冬小麦返青期的冠层叶片叶绿素分布情况,适用于作物长势空间分布的精准管理决策制定的信息支持;"绿峰"Rλgreen模型的空间预测能力稍差,但模型构建所需要的信息量较少,适合于冬小麦返青期长势情况空间分布的预估,对于快速建立空间长势评价体系有一定的应用价值。The first derivative curve of reflectance spectrum was calculated by measuring canopy leaf reflectance spectrum at returning green stage in winter wheat and the vegetation indexes were established by analyzing the curve’s local extreme values and relationship between their corresponding reflectivity and chlorophyll content,then,the predictive model of chlorophyll content was built according to different indexes,and finally the space predictive ability was analyzed based on GPS information and compared with the predictive effect of the predictive model to provide the theoretical base for precision management of winter wheat.The results showed that there were more local extreme values in the first derivative spectrum of canopy leaf reflectance spectrum and the reflectivity and vegetation indexes established from local extreme values was of the better predictive effect for the predictive model of chlorophyll content.R 2 value （0.743 5）was calculated by the NDVI（λgreen ,λrd ）predictive model established by using “green peak”and “red valley”of canopy spectrum curves,which can meet the demand of single-point prediction.The predictive model established from Rλgreen “green peak”and NDVI （λgreen ,λrd ）vegetation indexes was of a certain space predictive ability.NDVI （λgreen ,λrd ）with good space predictive ability cloud reflect the chlorophyll distribution status of the canopy leaves,which can support information for decision-making of precision management of crop growth space distribution.The Rλgreen model with a certain space predictive ability was suited to estimation of space distribution of winter wheat growth at returning green stage, which is of the application value in quick establishment of the space growth evaluation system.

关 键 词：冬小麦 返青期 光谱曲线 绿峰 

分 类 号：S24[农业科学—农业电气化与自动化] TP7[农业科学—农业工程]